By creating an integrated simulation environment that models the underlying structure of a pharmaceutical enterprise portfolio it becomes possible to identify the optimal longitudinal allocation of finite resources across the constellation of available investment opportunities. The implementation of a hybrid approach that integrates multiple modeling techniques and analytic disciplines allows for a comprehensive environment that captures the underlying dynamics that drive observed market behavior. The implementation of an object oriented model structure constrains the models complexity by supporting dynamic re-use of both structure and logic.

In recent US Census data widely reported in the press “Hispanics” have become the largest minority group in the US. Using simulation modeling technology we look at some of the structural forces that shape the characteristics of the Hispanic population. The model creates a simulated Hispanic population whose level of acculturation to the broader population of which it is a part dynamically varies according to individual choice. The modeling technique used draws on both System Dynamic and Agent based paradigms both supported by innovative AnyLogic software. The representative Hispanic population is disaggregated down to the individual level as individual agents. Each agent makes choices stochastically as modulated by its current state and the outside environment that it is in.

Mathematical modeling is a relatively new but fast developing area of HIV studies providing researchers with an additional dynamical dimension in epidemiological work that allows scientists to simulate the consequences of various intervention and prevention scenarios. We illustrate these concepts by presenting a model that describes Injecting Drug Users (IDU) networks, injecting behavior and HIV/HCV spread within the networks. This individual-based (also called agent-based) model is used to investigate the impact of the introduction of Integralcannula syringes (ICS) instead of commonly used Detachable Needle syringes (DNS). Laboratory experiments have shown that ICS retain approximately 1000 times less residual blood (<.001 ml vs. 1ml) following injection and rinsing than DNS thereby decreasing risk of HIV/NCV transmission by nearly 100 times after 2 rinses.

Mathematical modeling is a relatively new but fast developing area of substance use field providing researchers with additional dynamical dimension in epidemiological work and allowing scientists to simulate the consequences of various intervention and prevention scenarios. We illustrate these concepts by presenting two models. The first model describes Injecting Drug Users (IDU) networks, injecting behavior and HIV/HCV spread among the networks. The size, structure of the networks as well as frequency of injecting and HIV risks were obtained from published literature on urban IDU networks. This individual-based model was used to investigate the impact of introduction of Integral-cannula syringes (ICS) instead of commonly used Detachable Needle syringes (DNS).

This paper may be considered as a practical reference for those who wish to add (now sufficiently matured) Agent Based modeling to their analysis toolkit and may or may not have some System Dynamics or Discrete Event modeling background. We focus on systems that contain large numbers of active objects (people, business units, animals, vehicles, or even things like projects, stocks, products, etc. that have timing, event ordering or other kind of individual behavior associated with them). We compare the three major paradigms in simulation modeling: System Dynamics, Discrete Event and Agent Based Modeling with respect to how they approach such systems. We show in detail how an Agent Based model can be built from an existing System Dynamics or a Discrete Event model and then show how easily it can be further enhanced to capture much more complicated behavior, dependencies and interactions thus providing for deeper insight in the system being modeled.

The creation of IT simulation models for uses such as capacity planning and optimization is becoming more and more widespread. Traditionally, the creation of such models required deep modeling and/or programming expertise, thus severely limiting their extensive use. Moreover, many modern intelligent tools now require simulation models in order to carry out their function. For these tools to be widely deployable, the derivation of simulation models must be made possible without requiring excessive technical knowledge.

This paper explores the problem of fragmenting social networks enabled by spatial distancing between distinct socioeconomic classes. Such fragmentation is evidenced by the experience of urban sprawl without population growth. We develop a prototype model to examine the spatial dynamics of social network evolution in the face of neighborhood migration. This model draws upon the small world analogy by using an initial template of connections that are “rewired” over time. Spatially, connections are established for neighborhood proximity. Socially, connections are added based upon similarity of economic class.

This paper presents a hybrid simulation model for the management of an eye condition called age-related macular degeneration, which particularly affects the elderly. The model represents not only the detailed clinical progression of disease in an individual, but also the organization of the hospital clinic in which patients with this condition are treated and the wider environment in which these patients live (and their social care needs, if any, are met). The model permits a ‘whole system’ societal view which captures the interactions between the health and social care systems

The share of renewable energy sources in energy production is growing steadily. Domestic homes can be equipped with solar panels, micro combined heat and power systems, batteries, and they can become adaptive consumers. They can also deliver energy to the grid and react to the energy supply. This paper presents a hybrid simulation approach for the analysis of a grid of domestic homes equipped with different technological options with respect to efficiency and costs. For energy storage and energy flows the system dynamics modeling paradigm is used whereas control decisions are modeled as statecharts. The highly intermittent solar irradiation and also the electric power and heat demands are implemented as stochastic models. The component-based design allows for quick creation of new case studies. As examples, different homes with batteries, micro combined heat and power systems, or energy carrier carbazole as energy storage are analyzed